Main Page

Bangham Lab - Home

Current activity: a collaboration with the CoenLab with the aim of understanding how patterns of gene activity in biological organs influence the developing shape. The BanghamLab is focussed on the conceptual underpinning: concepts captured in computational growth models, experimental data visualisation and analysis.

Computational biology toolboxes

GFtbox

<imgicon>GPT_thumbnail2.png|120px|GFtbox</imgicon>

For modelling the growth of shapes. Details: what? How? Where? Tutorials: from the beginning Workshop Examples: from publications Download from SourceForge Ready Reference Manual (PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed Matlab 30 day free trial and student edition) Comment on results. R. Grant (2011) 'Taking Shape' TheScientist, 25:18

GFtbox is an implementation of the Growing Polarised Tissue Framework for understanding and modelling the relationship between gene activity and the growth of shapes such leaves, flowers and animal embryos. A paper describing the method and the software has appeared in PLoS Computational Biology. The GPT-framework was used to capture an understanding of (to model) the growing Snapdragon flower. The Snapdragon model was validated by comparing the results with other mutant and transgenic flowers. The icon shows an asymmetrical outgrowth. Conceptually, it is specifed by two independent patterns under genetic control: a pattern of growth and a pattern of organisers. The outgrowth arises from a region of extra overall growth. Growth is aligned along axes set by two interacting systems. Organisers at the ends of the mesh create a lengthwise gradient. This gradient interacts with the second due to an organiser that generates polariser in a region that becomes the tip of the outgrowth.

VolViewer

<imgicon>VolViewer-logo.png|120px|VolViewer</imgicon>

For viewing and measuring biological images. Details (Windows, Mac, Linux)

VolViewer uses OpenGL and Qt to provide a user friendly application to interactively explore and quantify multi-dimensional biological images. It has been successfully used in our lab to explore and quantify confocal microscopy and optical projection tomography images. It is open-source and is also compatible with the Open Microscopy Environment (OME).